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Archive of posts filed under the Political Science category.

Election Scenario Explorer using Economist Election Model

Ric Fernholz writes: I wanted to tell you about a new website I built together with my brother Dan. The 2020 Election Scenario Explorer allows you to explore how electoral outcomes in individual states influence the national election outlook using data from your election model. The map and tables on our site reveal some interesting […]

Taking the bus

Bert Gunter writes: This article on bus ridership is right up your alley [it’s a news article with interactive graphics and lots of social science content]. The problem is that they’re graphing the wrong statistic. Raw ridership is of course sensitive to total population. So they should have been graphing is rates per person, not […]

Election forecasts: The math, the goals, and the incentives (my talk this Friday afternoon at Cornell University)

At the Colloquium for the Center for Applied Mathematics, Fri 18 Sep 3:30pm: Election forecasts: The math, the goals, and the incentives Election forecasting has increased in popularity and sophistication over the past few decades and has moved from being a hobby of some political scientists and economists to a major effort in the news […]

Coronavirus disparities in Palestine and in Michigan

I wanted to share two articles that were sent to me recently, one focusing on data collection and one focusing on data analysis. On the International Statistical Institute blog, Ola Awad writes: The Palestinian economy is micro — with the majority of establishments employing less than 10 workers, and the informal sector making up about […]

“Congressional Representation: Accountability from the Constituent’s Perspective”

Steve Ansolabehere and Shiro Kuriwaki write: The premise that constituents hold representatives accountable for their legislative decisions undergirds political theories of democracy and legal theories of statutory interpretation. But studies of this at the individual level are rare, examine only a handful of issues, and arrive at mixed results. We provide an extensive assessment of […]

Information, incentives, and goals in election forecasts

Jessica Hullman, Christopher Wlezien, and I write: Presidential elections can be forecast using information from political and economic conditions, polls, and a statistical model of changes in public opinion over time. We discuss challenges in understanding, communicating, and evaluating election predictions, using as examples the Economist and Fivethirtyeight forecasts of the 2020 election. Here are […]

Post-stratified longitudinal item response model for trust in state institutions in Europe

This is a guest post by Marta Kołczyńska: Paul, Lauren, Aki, and I (Marta) wrote a preprint where we estimate trends in political trust in European countries between 1989 and 2019 based on cross-national survey data. This paper started from the following question: How to estimate country-year levels of political trust with data from surveys […]

Problem of the between-state correlations in the Fivethirtyeight election forecast

Elliott writes: I think we’re onto something with the low between-state correlations [see item 1 of our earlier post]. Someone sent me this collage of maps from Nate’s model that show: – Biden winning every state except NJ – Biden winning LA and MS but not MI and WI – Biden losing OR but winning […]

More on that Fivethirtyeight prediction that Biden might only get 42% of the vote in Florida

I’ve been chewing more on the above Florida forecast from Fivethirtyeight. Their 95% interval for the election-day vote margin in Florida is something like [+16% Trump, +20% Biden], which corresponds to an approximate 95% interval of [42%, 60%] for Biden’s share of the two-party vote. This is buggin me because it’s really hard for me […]

Update on social science debate about measurement of discrimination

Dean Knox writes: Following up on our earlier conversation, we write to share a new, detailed examination of the article, Deconstructing Claims of Post-Treatment Bias in Observational Studies of Discrimination, by Johann Gaebler, William Cai, Guillaume Basse, Ravi Shroff, Sharad Goel, and Jennifer Hill (GCBSGH). Here’s our new paper, Using Data Contaminated by Post-Treatment Selection?, […]

The NBA strike and what does it take to keep stories in the news

I was talking with someone about that NBA strike and he asked if I thought it was pointless given that they went back to work the next day. My take on it was, no, I think that doing a temporary strike was good tactics. Not necessarily for economic reasons—I have no idea about that—but from […]

FDA statistics scandal update

The other day we reported on the director of the FDA who got embarrassed after garbling some statistics at a news conference. At the time, I wrote: The commissioner of the FDA might well too busy to be carefully reading the individual studies. I assume the fault is with whatever assistant prepared the numbers for […]

Florida. Comparing Economist and Fivethirtyeight forecasts.

Here’s our current forecast for Florida: We’re forecasting 52.6% of the two-party vote for Biden, with a 95% predictive interval of approx [47.0%, 58.2%], thus an approx standard error of 2.8 percentage points. The 50% interval from the normal distribution is mean +/- 2/3 s.e., thus approx [50.7%, 54.5%]. Yes, I know these predictive distributions […]

Some thoughts inspired by Lee Cronbach (1975), “Beyond the two disciplines of scientific psychology”

I happened to come across this article today. It’s hardly obscure—it has over 3000 citations, according to Google scholar—but it was new to me. It’s a wonderful article. You should read it right away. OK, click on the above link and read the article. Done? OK, then read on.

Comments on the new fivethirtyeight.com election forecast

A colleague pointed me to Nate Silver’s election forecast; see here and here: The headline number The Fivethirtyeight forecast gives Biden a 72% chance of winning the electoral vote, a bit less than the 89% coming from our model at the Economist. The first thing to say is that 72% and 89% can correspond to […]

This is your chance to comment on the U.S. government’s review of evidence on the effectiveness of home visiting. Comments are due by 1 Sept.

Emily Sama-Miller writes: The federally sponsored Home Visiting Evidence of Effectiveness (HomVEE) systematic evidence review is seeking public comment on proposed updates to its standards and procedures. HomVEE reviews research literature on home visiting for families with pregnant women and children from birth to kindergarten entry, and its results are used to inform federal funding […]

Probabilistic forecasts cause general misunderstanding. What to do about this?

The above image, taken from a site at the University of Virginia, illustrates a problem with political punditry: There’s a demand for predictions, and there’s no shortage of outlets promising a “crystal ball” or some other sort of certainty. Along these lines, Elliott Morris points us to this very reasonable post, “Poll-Based Election Forecasts Will […]

Don’t say your data “reveal quantum nature of human judgments.” Be precise and say your data are “consistent with a quantum-inspired model of survey responses.” Yes, then your paper might not appear in PNAS, but you’ll feel better about yourself in the morning.

This one came up in a blog comment by Carlos; it’s an article from PNAS (yeah, I know) called “Context effects produced by question orders reveal quantum nature of human judgments.” From the abstract: In recent years, quantum probability theory has been used to explain a range of seemingly irrational human decision-making behaviors. The quantum […]

Kafka comes to the visa office

Paul Alper points us to this news article by Catherine Rampell about “a Kafkaesque new processing policy for select categories of visas”: If any fields on a form are left blank, it will automatically be rejected. Even if it makes no sense for the applicant to fill out that field. For example, if “Apt. Number” […]

“Statistical Models of Election Outcomes”: My talk this evening at the University of Michigan

At the Inter-university Consortium for Political and Social Research this evening: Statistical Models of Election Outcomes We will discuss various political and statistical aspects of election forecasts: – How accurately can elections be forecast? – What information is useful in forecasting elections? – What sorts of elections are less predictable? – To the extent that […]